Electricity safety inspection data model optimization method based on concurrent access constraints

Teng Zhang; Jindou Yuan; Mingfeng Xue; Mingming Pan; Shuo Chen

doi:10.1117/12.2684640

21 July 2023 Electricity safety inspection data model optimization method based on concurrent access constraints

Teng Zhang, Jindou Yuan, Mingfeng Xue, Mingming Pan, Shuo Chen

Proceedings Volume 12717, 3rd International Conference on Artificial Intelligence, Automation, and High-Performance Computing (AIAHPC 2023); 1271722 (2023) https://doi.org/10.1117/12.2684640
Event: 3rd International Conference on Artificial Intelligence, Automation, and High-Performance Computing (AIAHPC 2023), 2023, Wuhan, China

Abstract

In the field of electricity safety inspection, with the increase of the scale and complexity of the business process, the business process has dynamic changes. But the data model is not adapted to the dynamic changes in the business process. Therefore, in the business process of concurrent access to the database, it is easy to lead to data access conflict, reduce database concurrent access efficiency, and lead to increased business development costs. At present, there are many research results in business processes and database optimization, but there are still some mature and perfect optimization of the theory of databases, which can consider the optimization of business processes and business process data models. The data model optimization algorithm proposed in this article can be used to reduce database access conflicts of concurrent business processes, so that the data model can adapt to the dynamic changes in the business process, thereby improving the efficiency of concurrent access to the database.

Citation Download Citation

Teng Zhang, Jindou Yuan, Mingfeng Xue, Mingming Pan, and Shuo Chen "Electricity safety inspection data model optimization method based on concurrent access constraints", Proc. SPIE 12717, 3rd International Conference on Artificial Intelligence, Automation, and High-Performance Computing (AIAHPC 2023), 1271722 (21 July 2023); https://doi.org/10.1117/12.2684640

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